Abstract
A problem of no-reference image visual quality assessment when images are corrupted by noise is considered in this paper. A specialized image set is proposed for the following two tasks: automatic verification of sensitivity of no-reference image visual quality metrics to noise, and analysis of blind noise level estimation methods. As a result, a method to improve the sensitivity of a given no reference quality metric to the presence of noise is proposed by combining this metric with a noise level estimator. The proposed method allows to significantly decrease a probability of wrong quality predictions for noisy images. Efficiency of usage of different noise level estimators in the proposed combined metrics is analyzed.
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Bahnemiri, S.G., Ponomarenko, M., Egiazarian, K. (2023). Improved Sensitivity of No-Reference Image Visual Quality Metrics to the Presence of Noise. In: Gade, R., Felsberg, M., Kämäräinen, JK. (eds) Image Analysis. SCIA 2023. Lecture Notes in Computer Science, vol 13885. Springer, Cham. https://doi.org/10.1007/978-3-031-31435-3_14
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